Abstract

In this paper, we consider two types of pricing option in financial markets using quasi Monte Carlo algorithm with variance reduction procedures. We evaluate Asian-style and European-style options pricing based on Black-Scholes model. Finally, some numerical results presented.

Highlights

  • The theory of finance, like many areas where advanced mathematics plays an important part, is undergoing a revolution aided and abetted by the computer and proliferation of powerful simulation and symbolic mathematical tools

  • We evaluate Asian-style and European-style options pricing based on Black-Scholes model

  • Monte Carlo and quasi Monte Carlo methods are ubiquitous in applications in the finance and insurance industry

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Summary

Introduction

The theory of finance, like many areas where advanced mathematics plays an important part, is undergoing a revolution aided and abetted by the computer and proliferation of powerful simulation and symbolic mathematical tools. Monte Carlo and quasi Monte Carlo methods are ubiquitous in applications in the finance and insurance industry They are often only accessible tol for financial engineers and actuaries when it comes to complicated price or risk computations, in particular for those that are based on many underlying [ref. As expected values play a central role in various areas of applications of probabilistic modeling, the Monte Carlo method has a widespread use Examples of such areas of application are the analysis and design of queuing systems (such as in supermarkets or in large factories), the design of evacuation schemes for buildings, the analysis of the reliability of technical systems, the design of telecommunication networks, the estimation of risks of investments or of insurance portfolios, just to name a few [1,2]. The problem of using Monte Carlo and quasi Monte Carlo methods for computational finance has been extensively studied [4,5,6,7,8]

Definition of Financial Mathematics
Quasi Monte Carlo Methods and Variance Reduction Techniques
Variance Reduction Techniques
N i 1 f
Control Variates

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